I want to evaluate a graph kernel designed for large graphs (> 10^6 nodes). Hence, I'm looking for suitable graph data sets, i.e., a set of (huge) graphs and corresponding classes.
Any ideas?
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What type of graphs are you looking for? Would twitter data help? – sheß Sep 17 '15 at 12:38
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@sheß: Both directed and undirected graphs are fine. Each graph should belong to a class so I can perform classification. Could you please elaborate on the twitter data. – Christopher Sep 17 '15 at 13:06
Try Stanford Large Network Dataset Collection
https://snap.stanford.edu/data/egonets-Facebook.html[
Directed graphs twitter is listed undirected and directed graphs.
Hope it answer your question.
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Thanks, I'm aware of SNAP. Unfortunately, most of the datasets consist of a single large graph. – Christopher Sep 17 '15 at 16:16
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Than will be need to build on your own. Check databricks graphX databricks-training.s3.amazonaws.com/… – n1tk Sep 17 '15 at 16:25
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@sb709: Let's say 100 graphs for each class (two classes are sufficient), each graph should have at least 10^6 nodes. – Christopher Sep 18 '15 at 13:02
